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libri-alpha-0.25-Temp-1-mse
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 16.7446
- Wer: 0.1212
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
122.8866 | 0.75 | 100 | 35.8349 | 0.1501 |
96.5187 | 1.49 | 200 | 31.6506 | 0.1453 |
88.8912 | 2.24 | 300 | 23.5288 | 0.1459 |
82.3478 | 2.99 | 400 | 20.1852 | 0.1386 |
74.9987 | 3.73 | 500 | 19.2132 | 0.1327 |
71.3929 | 4.48 | 600 | 18.6715 | 0.1320 |
67.5429 | 5.22 | 700 | 18.1638 | 0.1275 |
65.8387 | 5.97 | 800 | 17.9401 | 0.1274 |
62.2889 | 6.72 | 900 | 17.5666 | 0.1254 |
62.4649 | 7.46 | 1000 | 17.5202 | 0.1251 |
61.3213 | 8.21 | 1100 | 17.1763 | 0.1250 |
59.1153 | 8.96 | 1200 | 17.2310 | 0.1229 |
61.095 | 9.7 | 1300 | 17.0079 | 0.1228 |
61.0961 | 10.45 | 1400 | 16.8989 | 0.1214 |
59.0814 | 11.19 | 1500 | 16.9785 | 0.1195 |
58.3763 | 11.94 | 1600 | 17.0034 | 0.1198 |
57.9529 | 12.69 | 1700 | 16.8352 | 0.1203 |
56.6213 | 13.43 | 1800 | 16.8661 | 0.1206 |
56.4495 | 14.18 | 1900 | 16.8180 | 0.1216 |
54.3606 | 14.93 | 2000 | 16.7446 | 0.1212 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0